{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "grades = ['A', 'B', 'C', 'D', 'E', 'F']\n",
    "students_count = [20, 30, 10, 5, 8, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 6 artists>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.bar(grades, students_count, color=['green', 'gray', 'gray', 'gray', 'gray', 'red'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('Grades Bar Plot for Biology Class')\n",
    "plt.xlabel('Grade')\n",
    "plt.ylabel('Num Students')\n",
    "plt.bar(grades, students_count, color=['green', 'gray', 'gray', 'gray', 'gray', 'red'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 6 artists>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(grades, students_count, color=['green', 'gray', 'gray', 'gray', 'gray', 'red'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
